Producing Volunteered Geographic Information from Social Media for LBSN Improvement

Abstract

Volunteered Geographic Information (VGI) emerged from the widespread of devices featuring GPS and Internet connectivity around the world. It has enabled the easier and increased production of spatial data, and a deeper engagement of people with everything involving location. Such scenario has led to the emergence of Location-Based Social Networks (LBSN), which allow users to be assigned to space related content. LBSN environments have proved to be quite useful, however, keeping users willing to contribute (i.e., maintaining such environments in continuous operation) has appeared to be challenging. In addressing this issue, we have considered applying Geographical Information Retrieval (GIR) techniques to produce VGI from social media streams on the Web, aiming to improve LBSN with valuable up-to-date content in an automated way. We rely on GIR techniques such as geoparsing the message bodies instead of considering previously geotagged information since we cannot ensure that an embedded geolocation is the same location that the messages refers to. An artifact for automatically producing VGI based on social media content is described and validated using a real-world case study. We harvested tweets during the FIFA Confederations Cup and tried to produce valuable VGI from the message stream. Our results proved to be promising for leveraging VGI from social media.